Abstract
This paper simulates Companies' ego networks on Twitter, meaning the companies' number and type of followers. Evident from our data, we show that followers' distribution, in our focus, is neither scale free nor random, thus common network simulations cannot be used to mimic observed data. We present novel rate equations model to capture the complex dynamics of these ego networks.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
| Editors | Ravi Kumar, James Caverlee, Hanghang Tong |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 174-177 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781509028467 |
| DOIs | |
| State | Published - 21 Nov 2016 |
| Event | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States Duration: 18 Aug 2016 → 21 Aug 2016 |
Publication series
| Name | Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
|---|
Conference
| Conference | 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 |
|---|---|
| Country/Territory | United States |
| City | San Francisco |
| Period | 18/08/16 → 21/08/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.
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